Power BI Project For Beginners | Sales Insights Data Analysis Project - 2 - Data Discovery

Summary

This video script outlines a project planning approach using the AIMS grid, a tool for effective project management. It details the process of identifying pain points, engaging stakeholders, defining end results, and setting success criteria. The script discusses a scenario where AtliQ Hardware uses AIMS to tackle data analytics challenges, involving teams like IT (Falcons) and data analysts (Data Masters). It emphasizes the importance of integrating data sources, such as MySQL, into Power BI for real-time analytics and dashboard creation. The video also hints at the next topic: data cleaning and merging within Power BI, assuring that even beginners can easily grasp these concepts.

Takeaways

• 📈 AIMS grid is introduced as a project management tool with four components: Purpose, Stakeholders, End Result, and Success Criteria.
• 🤝 Stakeholders identified for the project include marketing, sales, IT, and data analytics teams within AtliQ hardware.
• 🎯 The project's end result is envisioned as a Power BI dashboard providing real-time sales information to sales directors and regional managers.
• 📉 A key success criterion is reducing costs by 10%, particularly by minimizing manual work and reliance on BPO companies for data processing.
• 👨‍💻 The IT team, referred to as 'Falcons', owns the sales management system and will collaborate with the data analytics team, 'Data Masters', for the project.
• 🔌 The data analytics will utilize the MySQL database from the sales management system as a data source for the Power BI dashboard.
• 🚀 The script suggests creating a data warehouse for high data volumes to prevent affecting the performance of the OLTP system.
• 🛠 ETL (Extract, Transform, Load) processes are crucial for transforming data from OLTP systems into a format suitable for analytics.
• 🧼 Data cleaning and merging, also known as data wrangling or munging, will be addressed in the next video, with Power BI being the tool of choice.
• 📚 The video promises that even without prior knowledge of Power BI, viewers will be able to learn and use it effectively, likening it to 'Excel on steroids'.

Q & A

What is the main topic of the video script?

The main topic of the video script is project planning using the AIMS grid in the context of a data analytics project for a company named AtliQ Hardware.

Who is Bhavin Patel in the script?

Bhavin Patel is the Sense Director of AtliQ Hardware who recognizes the need for a data analytics project to address certain pains and possible solutions.

What does AIMS stand for in the context of the video?

AIMS stands for a project management tool with four components: Purpose, Stakeholders, End Result, and Success Criteria.

What are the four components of the AIMS grid?

The four components of the AIMS grid are Purpose, Stakeholders, End Result, and Success Criteria.

What is the role of the IT head or head of the data department in the project planning meeting?

The IT head or head of the data department is involved in brainstorming on project planning using the AIMS grid to determine the approach and execution of the data analytics project.

Which teams are involved in the data analytics project according to the script?

The teams involved in the data analytics project include the marketing team, sales team, IT team (software engineers), and the data analytics team.

What is the end result that AtliQ Hardware aims to achieve with the data analytics project?

The end result that AtliQ Hardware aims to achieve is a Power BI dashboard that provides real-time information on sales numbers for the sales director and regional managers.

What are the success criteria defined for the project in the AIMS grid?

The success criteria include reducing costs by 10% and eliminating the need for manual work in merging Excel files, thereby saving business time and cost.

What is the role of the 'Falcons' in the context of the data analytics project?

The 'Falcons' is a team of software engineers at AtliQ Hardware who own the sales management system and the MySQL database, which is the source for the data analytics project.

What is the significance of a data warehouse in the context of high data volume?

A data warehouse is significant for high data volume as it allows for the extraction, transformation, and loading (ETL) of data from the OLTP system (MySQL in this case) into a format that is optimized for analytical queries without affecting the performance of the primary business operations.

What is the next step in the project after defining the AIMS grid?

The next step is to discuss with the data analyst team (Data Masters) and the IT team (Falcons) on how to solve the problem using the MySQL database and integrating it with Power BI to build the dashboard.

What is the approach to data analysis if the required data is not available within the organization?

If the required data is not available, data analysts will spend time capturing the necessary information needed to perform the data analysis.

What will be covered in the next video according to the script?

The next video will cover data cleaning and data merging, also known as data wrangling or data munging, using Power BI.

Why is the term 'data wrangling' or 'data munging' used in the script?

The terms 'data wrangling' or 'data munging' are used to describe the process of cleaning and merging data, which is made easy in Power BI and does not require prior background knowledge.

Outlines

00:00

📈 Project Planning with AIMS Grid

This paragraph introduces the concept of project planning using the AIMS grid, a project management tool. It discusses the process initiated by Bhavin Patel, a sense director, who calls a meeting with various department heads to brainstorm on data analytics projects. The AIMS grid is explained with its four components: purpose, stakeholders, end result, and success criteria. The purpose is to identify the pain points, stakeholders include marketing, sales, IT, and data analytics teams, the end result aims for a Power BI dashboard for real-time sales data, and the success criteria are set to reduce costs and improve efficiency. The paragraph also touches on the potential outsourcing to service-based companies if in-house teams are unavailable.

05:05

🔍 Data Integration and Analytics

The second paragraph delves into the technical aspects of data integration and analytics. It describes the collaboration between the 'Falcons' IT team, responsible for the sales management system and its MySQL database, and the 'Data Masters' data analytics team. The data from the MySQL database, which is an OLTP system, is considered critical for business operations. The paragraph explains the common practice of creating a data warehouse for analytical purposes to avoid affecting the performance of the OLTP system. It also covers the ETL process, using tools like Apache NiFi or Python, to transform data into a format suitable for analytics. The goal is to build a Power BI dashboard without creating a separate data warehouse, directly connecting Power BI to the MySQL database.

10:08

🛠️ Data Wrangling in Power BI

The final paragraph assures viewers that even without a background in Power BI, they will be able to quickly learn the necessary skills for data wrangling or munging, which are terms used to describe the process of cleaning and preparing data for analysis. The speaker emphasizes that Power BI is user-friendly and similar to Excel, making it accessible for beginners. The next video in the series will focus on data cleaning and merging within Power BI, promising a straightforward approach to these tasks.

Keywords

💡AIMS grid

AIMS grid is a project management tool that helps in organizing and planning projects effectively. It consists of four components: purpose, stakeholders, end result, and success criteria. In the video, AIMS grid is used to brainstorm and structure the data analytics project for AtliQ Hardware, ensuring that all aspects of the project are considered and clearly defined.

💡Pain point

A pain point refers to a problem or challenge that an organization faces which needs to be addressed. In the context of the video, the pain point for AtliQ Hardware is the inefficiency in their sales data management and the need for improved analytics to drive better business decisions.

💡Stakeholders

Stakeholders are individuals or groups who have an interest or involvement in a project. The video mentions the marketing team, sales team, IT team, and data analytics team as stakeholders in the project, emphasizing the collaborative nature of the project planning process.

💡End result

The end result is the desired outcome or goal of a project. For AtliQ Hardware, the end result is a Power BI dashboard that provides real-time sales information, which is a clear and specific objective that guides the project's direction.

💡Success criteria

Success criteria are the metrics or conditions that define whether a project has been successful. The video outlines reducing costs by 10% and eliminating manual Excel file merging as success criteria for the project, indicating a shift towards more efficient data management practices.

💡Data analytics team

A data analytics team is a group of professionals who specialize in analyzing data to support business decisions. In the video, AtliQ Hardware's data analytics team, referred to as 'data masters,' is responsible for building the Power BI dashboard and ensuring the project meets its success criteria.

💡Software engineers

Software engineers are professionals who design, develop, and maintain software systems. The video introduces the 'Falcons' as the software engineering team at AtliQ Hardware, who manage the sales management system and its underlying MySQL database.

💡OLTP (Online Transaction Processing)

OLTP refers to systems that manage real-time transactions, such as sales records in a database. The video mentions that the MySQL database used by AtliQ Hardware is an OLTP system, critical for the company's day-to-day sales operations.

💡ETL (Extract, Transform, Load)

ETL is the process of extracting data from a source, transforming it to fit analytical needs, and loading it into a target system. The video discusses the use of ETL for preparing data from the MySQL database for analytical purposes in a data warehouse.

💡Data warehouse

A data warehouse is a system designed to support analytical queries and reporting. In the video, it is suggested that data from the OLTP system could be transformed and stored in a data warehouse for more efficient and effective data analysis.

💡Power BI

Power BI is a business analytics service by Microsoft that provides interactive visualizations and business intelligence capabilities. The video describes the use of Power BI to build a dashboard for AtliQ Hardware, emphasizing its ease of use and integration with existing SQL databases.

💡Data wrangling/Data munging

Data wrangling or data munging refers to the process of cleaning, structuring, and enriching raw data into a desired format for analysis. The video mentions that data cleaning and merging will be performed in Power BI, indicating an important step in the data preparation process.

Highlights

Introduction to project planning using AIMS grid for data analytics projects.

Identification of pain points and the need for a data analytics project in AtliQ hardware.

The role of the IT head and data department in initiating a data analytics project.

Explanation of AIMS grid as a project management tool with four components.

The importance of defining the purpose of the project in the AIMS grid.

Identifying stakeholders such as marketing, sales, IT, and data analytics teams.

The significance of the end result in project planning and its impact on decision-making.

Desired outcome of the project: a Power BI dashboard for real-time sales information.

Defining success criteria using AIMS grid to measure project effectiveness.

The goal of reducing costs by 10% through efficient data management.

The inefficiency of manual Excel file merging and the need for automation.

Potential outsourcing of data analytics to service-based companies if in-house teams are unavailable.

The concept of a data warehouse for handling high data volumes and analytical queries.

ETL process explanation: Extract, Transform, and Load data for analytics.

Use of tools like Apache NiFi, Python, and Informatica for data transformation.

The role of data analysts in capturing and preparing necessary data for analysis.

Upcoming discussion on data cleaning, merging, and wrangling in Power BI.

Assurance that Power BI is user-friendly and accessible even without prior knowledge.

Transcripts

in last video we looked at problem statement in this video we are going to 

look at project planning using AIMS grid and data discovery after bhavin patel 

who is a sense director of at lake hardware realizes the pains and the 

possible solution he will call a couple of people like an 

IT head or a head of data department and he will should live a meeting on how 

exactly we should do this data analytics project and after those people are in 

the room together they will brainstorm on project planning using AIMS grid now 

what is AIMS grid AIMS grid is a project management tool and it has four 

components to it the first component is purpose so first we want to determine 

what is our pain point what do we want to do exactly the second component is 

the stakeholders so in this project who all will be involved so here of course 

the marketing team the sales team who is facing these issues will be involved the 

IT team will be involved so the IT team is basically the team of software 

engineers that AtliQ hardware has and the data analytics teams will also be 

involved so we are assuming that AtliQ hardware or already has a data analysis 

team in-house they also have an in-house team of software engineers usually some 

companies don't keep this team in-house in in that case they will outsource 

their work to some service based companies such as Accenture enforces TCS 

etcetera so if you want to assume that this project is exported to those 

companies then those service based companies will manage the whole thing 

but here for our project we are assuming that all these teams are available 

within AtliQ hardware the third component to Ames grid is the end result 

after the project is over what do you want to achieve so we need to define 

that very clearly it cannot be a vague statement that I want to generate sales 

inside in our case the end product be a power bi dashboard something that 

our sales director or even Regional Managers can go and look into and it 

gives you a real-time information on your sales numbers the fourth component 

would be the success criteria after the project is over unless that you have 

spent few million dollars how do you define that the project was successful 

AIMS grid allows you to do that by exactly specifying your success criteria 

so in this case our criteria would be we want the cost to go down by 10% also 

until now the sales team and Regional Managers have been giving this 

information in Excel file sometimes if Regional Manager wants the information 

in more precise way there will be couple of people who will be manually working 

on merging these Excel files you know so there is lot of time that is being 

wasted today so we want to save our business time and cost on those 

operations there are many BPO companies today that exist and all those companies 

do is they will get couple of Excel files they will do merging they will do 

some Excel formulas you know they do lot of manual work so many organizations end 

up spending a lot of money on these manual works and AtliQ hardware is one 

of them so we want to reduce cost on that front and one other success 

criteria could be we want to bump up ourselves by let's say five person so 

after we do all this hard work build a dashboard we want to use it for three 

months and we want to make sure that we have achieved all these results defined 

by success criteria so the AIMS grid is an extremely useful tool for any project 

managers and leaders which can help you Mon manage the project in an effective 

way for AIMS grid I have this nice youtube video where this person explains 

the sames grid in a very simple manner so I would suggest that you watch this 

video it will be helpful in terms of improving your 

project management skills so now you have defined AIMS grid you know exactly 

what needs to happen the then self director Wilke will call the data 

analyst team and he will start discussing that how we can solve this 

problem he will also call the IT team now just to be fancy I have given this 

fancy name to our IT team let's call them Falcons so Falcons here is a team 

of software engineers who own the sales management system so AtliQ hardware 

has this sales management system which is just a simple software that is a 

keeping track of all the sales number so whenever they sell any computer or any 

hard days in any local region this software is printing the invoice so it 

has all the records stored in a MySQL database and this database and this 

application is or owned by this Falcons team over data analyst team is called 

data masters so the data masters will reach out to Falcons and say hey we want 

to use your SQL database because this is the database which has all the records 

that we need for our analytics and what we'll do is we'll integrate MySQL 

basically we will use MySQL as a source in our power bi tool and we will build 

dashboard on top of it and Falcone's don't mind if I can say yeah go ahead 

and this is the approach we are going to use now in majority of the time when the 

data volume is high you want to make sure that your MySQL database is not 

affected by the queries that you are doing in your power bi so sometimes what 

people do is not sometimes actually many many times they will design a data 

warehouse okay so what is data warehouse so data 

warehouse is basically you take the data from MySQL which is also known as OLTP 

which is online transaction processing system it is a very critical system you 

cannot afford for that system to go down otherwise your regular sales operations 

and gets hampered right for you that means business is very important 

analytics is important but then it's a secondary thing so what people do is 

they pull the data from OLTP which is MySQL in our case they do all the 

transformation which is also called ETL which means extract transform and load 

and after doing that transformation they store the data in a data warehouse 

there are many data warehouse such as Tara data or snowflake and so on and for 

doing this transformation people use tools such as Apache knife I tell end or 

even Python and pandas by doing this transformation you are reformatting the 

data in a way that is best for performing analytical analytical queries 

because if you perform your query directly on MySQL database there are two 

problems one is if you cause that database to slow down then your 

mainstream business is affected second problem is the data stored in the 

OLTP is not often in a format that you want so you want to do lot of 

transformation such as currency conversation you want to remove the 

columns which are not needed there could be n number of transformation that you 

want to do and all of that happens in the ETL tools such as informatica or 

apache ni fi and for doing this they have the steam of data ingenious so data 

ingenious job is to do this transformation and maintain the data 

warehouse infrastructure and after that our data masters will come in play and 

data masters will pull the data from data warehouse and they will build 

the power bi dashboard for simplicity we are not going to build any data 

warehouse will have an SQL database and then we will directly plug power bi to 

that SQL database and build our dashboard now sometimes the data that 

you need for analytics might not be available in your organization at all so 

you might have to work on capturing that information so many times data analysts 

will spend their time and they will capture the required information that is 

needed to perform the data analysis so that's all I have for this video in the 

next video we are going to look at data cleaning and data merging this is also 

known as data wrangling or data munging whatever you want to call it we will do 

all of this in power bi itself now data munging data wrangling these are all 

sensitives do not worry actually it's very easy you already know it's just 

that people use these fancy terms and confuse you unnecessarily we are going 

to do all of this in power bi and trust me you don't need any prior background 

for this project even if you don't know anything about power bi it's perfectly 

fine power bi is very similar to excel actually it is literally excel on 

steroids and we will look into it it's it's very very easy even if you don't 

have any background you will be able to learn it very quickly